This page essentially gives an overview of the various splits already tried when a user enters the model building phase after data annotation and quality control steps.

Different parameters of the created splits on this page

• Split name

• Problem - This is the type of model you want to use for the model building phase. It includes: Attribute prediction, Label class prediction, Object detection, Image tag prediction, Instance segmentation, Semantic segmentation.

• Creation date

• Created by - This helps to track which user is experimenting with a particular model.

• Images - This value gives an idea of the number of images (Total, Train, Test, Validation) that were used for a particular set of experiments/model types.

• Experiments - Total number of experiments a user has carried out for a model type.

Actions you can perform on this page

• Open model dashboard if the split is clicked.
• Create a new split
• Delete - Delete a particular split